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With rapid advancement in aerial vehicle technologies, air taxi is drawing keen interest as a new type of transportation service. One of the necessary elements for air taxi-based transportation service system is a skyport, which is a designated area for take-off and landing of air taxis. In planning a skyport network for air taxi transportation system, it is important to consider midair congestion between air taxis. Severe congestion increases the risk of collisions, which in turn increases the complexity in scheduling and routing in the subsequent operations phase. In this study, we propose a novel hub location problem (HLP) that incorporates traffic congestion caused by intersecting vehicles along hub-to-hub arcs. Modeling congestion in an HLP formulation involves nonconvex bilinear terms, which makes it difficult to solve. We tackle this challenge by exploiting a property of an optimal solution and reformulating the original model to obtain a linear formulation. We also develop a heuristic algorithm based on a genetic algorithm to handle large-size problems for practical applications. Using the proposed model and solution methods, extensive experiments have been conducted to study optimal design of air taxi network under various environments. Our analyses demonstrate that viability of air taxi service is a complicated function of many factors including collision risk, system cost, airspace design, to name a few. Our model can offer quantitative understanding of such complex relationships to assess and develop strategies to improve the viability of an air taxi transportation system.

How do people come up with humorous ideas? In creative cognition research, exposure to good examples sometimes causes fixation (people get “stuck” on the examples) but other times sparks inspiration (people's responses are more creative). The present research examined the effects of funny and unfunny examples on joke production. A sample of 175 adults read scenarios that they completed with funny responses. All participants were instructed to be funny, but before responding they read (a) funny responses as examples of good responses to emulate, (b) unfunny responses as examples of poor responses to avoid, or (c) no examples. The participants’ own responses were rated for funniness and for similarity to the example responses, and response times were recorded. Reading either funny or unfunny examples, compared to no examples, caused people to come up with funnier jokes. Similarity to the examples was low in all conditions, so fixation was relatively modest, but people who saw unfunny examples spent more time coming up with their responses. Taken together, the findings support the growing literature showing that examples are often inspiring rather than constraining, and they imply that good and bad examples spark creative thought via different paths.